Principal Statistical Programmer – FSP, RWD/EPI

Job Responsibilities

• Providing support to the Epidemiology team by preparing Real World data, advising on data analytic strategies, and supporting stakeholders in various epidemiology analytic activities.

• Programming and conducting statistical analysis under the direction and supervision of epidemiologists/statisticians including data coding, creation of algorithms, linkage of datasets, and use of statistical packages or platforms.

• Supporting statistical programming to generate innovative means of data standardization, visualization, and reporting of observational data.

• Supporting Medical Affairs (e.g. observational studies leveraging RWD); Global Patient Safety and Risk Management (e.g., analysis to obtain background rates) for the development of regulatory/safety documents, and Clinical Development (e.g.; assessment of patient populations/ protocol feasibility).

• The position will partner with Epidemiologists to manage relationships with internal and external stakeholders.

• Being able to prioritize and manage work across multiple projects and stakeholders.

• Providing strong communication to ensure successful and timely project delivery.

• Solve technical problems with experience and expertise.

Requirements

• Master’s degree or PhD in related field (epidemiology, biostatistics, statistics, bioinformatics, economics) and 5+ years of experience conducting RWE analytics for pharma industry, CRO, or academic institution.

• Intermediate to expert level proficiency in SQL is a must. In addition, SAS or R proficiency is required.

• Deep expertise analyzing RWE data sources such as Optum (Clinformatics Datamart® and Market Clarity), Truveta and UK Biobank. Experience analyzing clinical trial and/or registry data is desirable.

• Familiarity with relational databases and proficient understanding of claims and ancillary file layouts.

• Experience with applied statistics including regression analysis (OLS, longitudinal, logistic, Cox, GLM/GEE), survival analyses (Kaplan-Meier, cumulative incidence, accelerated failure time models), and propensity weighting.

• Excellent project management skills; can prioritize multiple tasks and goals to ensure timely completion.

• Confident and competent when interacting with internal and external stakeholders.

• Strong written/verbal communication skills. Highly effective at summarizing and presenting key considerations and evidence.